A standard use case for Docker is to build a container to run a pre-built application so that the containerized app can be run on any Docker enabled host. The application and the container are sometimes developed and built separately. First the application is built, then a container is defined and built to include the application. However, it can be better to promote the Docker container to a first-class build artifact. That is, the build process always builds the deployed component and its container at the same time. This saves a manual build step and also ensures that the Docker container is always up to date with the latest application build. It allows us to easily develop and test against the Dockerized application directly – every build results in a new deployable container.

There are a number of ways to do this. This article looks at hooking the Docker tasks into the Maven build process.

CRUD REST services are the backbone of a microservice architecture. If we want to use microservices rather than monolithic applications, it’s essential that we can create a basic service with a minimum of effort. Spring Boot can be used to quickly create and deploy a new web service. Spring Data REST can be used to build out the REST interface based on a database entity model. Using both together allows us to create a running RESTful web service with zero custom Java code and no tricky XML.

This how-to describes how to build a RESTful web service as an executable JAR that provides CRUD operations against a single MySQL database table.

The Node.js website describes it as having “an event-driven, non-blocking I/O model that makes it lightweight and efficient”. Sounds lovely, but what’s it actually for?

Modulus’s excellent blog post – An Absolute Beginner’s Guide to Node.js provides some rather tasty examples. After covering the trivial examples (Hello world! and simple file I/O), it gets to the meat of what we’re about – an HTTP server. The simple example demonstrates a trivial HTTP server in Node.js in 5 lines of code. Not 5 lines of code compiled to an executable or deployed into an existing web server. 5 lines of code that can be run from a simple command. It then goes on to describe the frameworks and libraries that let you do really useful stuff.

This looks just the thing for implementing a new feature in the Spanners demo app: push notifications to all logged-in users when a spanner is changed.

Getting the details right when implementing password storage is critical. Some hash algorithms are vulnerable or just not suited to password hashing. If the salt is too short or predictable, it may be possible to retrieve the password from the hash. Any number of subtle bugs in coding could result in a password database that is vulnerable in one way or another. Fortunately, Spring Security includes password hashing out of the box. What’s more, since version 3.1, Spring Security automatically takes care of salting too.

This series of articles on Docker has so far covered a number of examples of creating and running individual Docker containers. We’ve also seen an example of how multiple Docker containers can be linked together using the –link command line flag.

Best practice for containerization suggests that each container does exactly one job. A full environment stack for a complex application may comprise many components – databases, web applications, web/micro services – each requiring its own container. Setting up the full working environment stack may require several lines of docker run commands, run in the right order, with just the right flags and switches set.

An obvious way to manage this is with a startup script. A neater solution is to use Docker Compose. Docker Compose allows multi-container applications to be defined in a single file and then started from a single command.

The previous posts in this series on Docker have looked at running containers to run services, specifically a web server and database server. However, Docker allows containers to be created, run, stopped and destroyed so cheaply that they can be used to run a single job. This job could be a script or even a single command. Unlike a service, a job will stop running when it’s complete. A container running a short lived job can be set to automatically stop and remove itself once the job is complete. If the job needs to be run again, it is reasonably efficient for Docker to start up a brand new container as required.

The previous post in this series on Docker looked at starting up containers built from predefined images provided by Docker Hub. In this, the second in the series, I’ll look at creating customized images tailored to my specific requirements. I’ll also look at how my custom image can be pushed to Docker Hub for others to use.

Docker is a containerization technology that’s been getting quite a bit of attention over the last year or two. It offers a more lightweight, flexible and repeatable solution to creating and running Virtual Machines (VMs). In this, the first in a series of posts on Docker, I’ll look at how to run an application inside of a pre-built container image.

A common requirement for secured applications is that admin / super users are able to login as any other user. For example, it may be helpful for a customer support analyst to access a system as if they were a real specific customer. The obvious way to do this is for the admin user to ask for the customer’s password or look it up in the password database. This is usually an unacceptable security compromise – no one should know a customer’s password except for the customer. And if the password database is implemented correctly it should be technically impossible for anyone – not even a system admin or DBA – to discover a user’s password.

An alternative solution is to allow admin users to login with their own unique username and password but allow them to then impersonate any other user. After the admin user has logged in, they can enter the username of another user and then view the application as if they were logged in as that user. Implementing user impersonation in this way also has the advantage that the system knows who has really logged in. If the system has an audit log, we can audit actions against the real admin user, rather than the impersonated user.